2. consume healthy foods (Brown and Hermann, 2005;
Clifford et al., 2009; Bukhari et al., 2011). Nevertheless,
home economics, which is the key discipline for the dis-
semination of food skills and knowledge and is the only
subject area that focuses on everyday life and meeting
basic needs in the school curriculum (Smith and De
Zwart, 2010), disappeared from many educational curric-
ula two or three decades ago or has been replaced by food
technology or more ‘scientific’ subjects (Goldstein, 2012).
Some forms of food knowledge have survived in school
health courses such as nutrition, though even this has
tended to focus on single nutrients (Jacobs and Tapsell,
2007), often completely failing to deal with more relevant
forms of nutrition knowledge required to cope with the
metabolic disease epidemic.
A report from the UK Cabinet Office in 2008, however,
marks a renewal of emphasis on food issues (UK Cabinet
Office, 2008). The report noted that food is integral to
environmental and agricultural policy, health and safety
and social and foreign policy. A key point made in the re-
port is that an integrated approach to food is required in
which there is understanding of the multifaceted roles of
food in daily life and in national and international affairs.
Thorough and wide knowledge of food is usually provided
in home economics curricula to enable future citizens
to choose safe and healthy foods that do not harm their
families, other humans or animals and the environment
(Smith and De Zwart, 2010).
Recently, there has been a renewal of interest in
school food education. For example, the Department
for Education in the UK has recently mandated compul-
sory cooking education for all children between 8 and
14 years (Department for Education, 2013). For this
movement to progress further, several questions need to
be answered.
(1) Which types of food education do citizens require?
We have conducted a series of studies of experts and citi-
zens to answer this question (available from the authors,
Worsley et al., 2013). Most consumers suggest a mix of to-
pics involving both the dissemination of skills and declara-
tive knowledge relating to several areas such as nutrition
and health, food safety, sustainable environments, mar-
keting, planning and preparation of meals and a number
of ethical issues (e.g. the treatment of animals in food pro-
duction). These topics were reviewed in detail in the
Labelling Logic report published by the Australian
Government in 2011 (Blewett et al., 2011).
(2) What are the influences on people’s food knowl-
edge? There has been relatively little examination of this
question. Most of the evidence to date focuses on demo-
graphic associations of various forms of nutrition knowl-
edge. Six studies suggest that women know more about
nutrition than men (Hendrie et al., 2008; Ozcelik and
Ucar, 2008; Grimes et al., 2009; Lin and Yen, 2010; Lin
et al., 2011; Choui et al., 2012). The relationship of nutri-
tion knowledge with age is more uncertain: five studies
have shown them to be positively related (Berg et al.,
2002; Hendrie et al., 2008; Grimes et al., 2009; Kresic
et al., 2009; Lin and Yen, 2010), two found negative asso-
ciations (Hendrie et al., 2008; Dickson-Spillman and
Siergrist, 2010), Bakhotmah (Bakhotmah, 2012) and
Charlton et al. (Charlton et al., 2010) found no associa-
tions, and Wardle et al. (Wardle et al., 2000) found that
middle-aged people had the highest level of knowledge.
Four studies have shown that duration of education is
positively related to nutrition knowledge (Hendrie et al.,
2008; Dickson-Spillman and Siergrist, 2010; Lin and
Yen, 2010); however, Grimes et al. found no association
(Grimes et al., 2009).
There has been little examination of other areas of food
knowledge though it might be expected that similar demo-
graphic trends might apply. One recent study we con-
ducted of Australians’ basic knowledge of Australian
agriculture revealed generally low levels of knowledge
and few gender, educational differences, although knowl-
edge did increase with age (Worsley et al., 2014). If similar
weak demographic associations are shown to apply to
other areas of food knowledge, then it would be possible,
for example, to focus communication efforts on demo-
graphic groups that have lower levels of knowledge.
(3) Does school education influence adults’ food
knowledge? The little amount of research into this ques-
tion mirrors the generally low priority given to food edu-
cation, despite the major physical, temporal and human
resources expended in school education in health and re-
lated curricula. To date, we have identified only one re-
port, from Ireland, which showed that home economics
education was associated with higher food safety knowl-
edge in adulthood (McCarthy et al., 2007). Probably
most people assume that school education imparts long-
lasting knowledge, but does it do so when it comes to
food knowledge? A closely related question is: Do the
different food-related curricula directed by different
regional education authorities result in higher levels and
different types of food knowledge among adults?
The main aims of this article, therefore, are to inves-
tigate the last two questions above, specifically:
(i) The influences on various forms of food knowledge in
adults, including likely demographic influences, as
well as the possible influence of health or home eco-
nomics education at school. Based on the literature
cited above, we expected that age, female gender, dur-
ation of education and the presence of children under
2 A. Worsley et al.
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3. 18 years of age in the household will be associated
with higher levels of knowledge. We also expected
that health or home economics education would also
be associated with greater levels of food knowledge
since these are the main subjects in the school curric-
ulum that communicate about food issues.
(ii) Whether the different curricula taught in the States of
Australia bring about different types and levels of knowl-
edge in adults. For many decades, the Australian States
have designed and taught their own health- and
food-related curricula, though there appears to have
been a shift about 20 years ago towards food technol-
ogy (Henry, 1990; Williams, 1994). Nevertheless, we
expected that State differences might be associated
with different types and levels of knowledge.
METHODS
Sampling and administration
Two studies were conducted in Australia as part of two
online surveys of the adult population. The first survey
was conducted in November 2011 (n = 2022) and the se-
cond in November and December in 2012 (n = 2146).
Both surveys were based on quota samples in which the
gender, age and education groups were represented to
match their proportions in the Australian population
(Australian Bureau of Statistics, 2012; Table 1). The par-
ticipants in each survey were selected from the Global
Market Insights (GMI) research database and invited to
participate via email. The GMI research database includes
individuals who have voluntarily enrolled themselves
to take part in surveys in return for reward points.
Participants who agreed to be involved in the research
were emailed a link to an online Food and Health
Concerns Survey. Both surveys used cross-sectional de-
signs and were part of a larger project examining the
predictors of Australian consumers’ food knowledge.
GMI recruits its panels by using a mixture of methods
including opt-in email, co-registration, e-newsletter cam-
paigns, search engine marketing and traditional banner
placements. A variety of checks are used to ensure the
quality of the survey data. These include confirmation of
email addresses and locations, various fraud-screening
measures and the barring of previously rejected respondents.
Ethics permission was granted by the Deakin University
Faculty of Health Human Ethics Committee (HEAG-H127:
2011 and HEAG-H137 2012).
Study 1 questionnaire
The Food Knowledge Survey 2011 was designed to exam-
ine how much Australian adults know about the compo-
nents of a healthy diet, the nutrient content and health
consequences of foods, safe food practices and a variety
of environmental and ethical food issues such as animal
welfare and climate change. The questionnaire included
the following items.
Nutrition knowledge
Twenty-six items were arranged in four broad sets relating
to knowledge of nutrition recommendations, nutrition
composition, nutrition function and food label knowl-
edge. Four choice and true/false response formats were
used. The responses were recoded as true or false (1, 0)
answers through reference to a previous validation study
conducted by us (available from the corresponding
author) as well as previous published studies. Nutrition
recommendation, nutrition composition, nutrition func-
tion and food label knowledge scores were derived by
summing the totals of correct answers for each section
and then dividing by the number of items in each section.
A total nutrition knowledge score was then derived by
summing the nutrition recommendations, nutrition com-
position, nutrition function and food label knowledge
scores (Table 2).
Food safety knowledge
Similar to the nutrition knowledge scores above, a food
safety knowledge score was derived by summing the cor-
rect/false recoded responses across the seven food safety
items (Worsley et al., 2013; Table 2).
Table 1: The demographic and education characteristics
of the respondents in Studies 1 and 2
Food survey
2011
total n = 2022
Food survey
2012
total n = 2146
Age (years) 43.6 (14.2) 45.9 (16.1)
Male (%) 1019 (50.4%) 1008 (47%)
Female (%) 1003 (49.6%) 1138 (53%)
Percentage who studied
health or home economics
at school (%)
1088 (53.8%) 898 (41.8%)
Presence of children under
18 years of age in the
household (%)
678 (33.5%) 672 (31.3%)
Percentage with university
education (%)
639 (31.6%) 769 (35.8%)
All values are presented as percentages except for mean (s.d.) for age.
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4. Table 2: Summary of regression analyses of the food knowledge scores in Studies 1 and 2
Nutrition function
knowledge score
Standardized β
Nutrition
recommendation
knowledge score
Standardized β
Nutrition composition
knowledge score
Standardized β
Total nutrition
knowledge score
Standardized β
Food label
knowledge score
Standardized β
Food safety
knowledge score
Standardized β
Environment and
ethics knowledge
score Standardized β
Study 1, 2011
R2
11.4% 15% 12.8% 15.4% 3.5% 5.3% 7.2%
Age 0.205**** 0.273**** 0.289**** 0.288**** 0.083**** 0.212**** 0.168****
Gender 0.178**** 0.201**** 0.140**** 0.174**** – – −0.84****
Education level 0.099**** 0.109**** 0.146**** 0.142**** 0.101**** 0.065**** 0.217****
Children 0.118**** – – 0.048** – – –
School health or home ec. 0.154**** 0.165**** 0.143**** 0.185**** 0.163**** 0.130**** 0.111****
Study 2, 2012
R2
3.4% 10.5% 12.8% 11.7% – 11.5% 3.8%
Age 0.111**** 0.240**** 0.268**** 0.235**** – 0.281**** 0.73***
Gender 0.064*** 0.207**** 0.221**** 0.215**** – 0.175**** –
Education level 0.115**** 0.077**** 0.140**** 0.137**** – – 0.152****
Children – – – – – – −0.056**
School home ec. 108**** 0.101**** 0.095**** 0.115**** – 0.106**** 0.123****
Notes: R2
= the proportion of variance in the knowledge scores accounted for by the predictor variables. Children: Presence of children under 18 years in the household; School home ec.: School home economics or a similar subject.
*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.
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5. Environmental and ethical knowledge
Again as for the previous forms of knowledge, the re-
sponses to the 31 items in this section were recoded and
summed to yield an environmental and ethical knowledge
score (Table 2). Full details of all the food knowledge items
used in Studies 1 and 2 are available from the authors.
Demographic and background information
The demographic characteristics of the respondents were
assessed by questions about gender (coded as 1 = male
and female = 2), age (a continuous variable but also
coded into age bands 1 = 18–29, 2 = 30 = 39, 3 = 40–49,
4 = 50–59, 5 = 60 and above), educational background
(1 = Year 11 or less, 2 = Completed Year 12, 3 = TAFE
or trade qualification, 4 = University qualification), home
economics/health studies completed at school (1 = no,
2 = yes) and presence of children under 18 years of age
in the respondent’s household (coded as 1 = no, 2 = yes;
Table 1).
Study 2 questionnaire
The Food Knowledge Survey 2012 was similar to that of
Study 1. The knowledge scores were calculated and coded
using the same procedures as those of the Study 1; how-
ever, because other predictive variables were included
in this study (Farragher, unpublished, available from
the authors), the number of knowledge items was reduced
though those included were the same as in Study 1. Thus,
there were 19 items about nutritional knowledge, 5 items
relating to food safety and 6 environmental knowledge
items. The scores derived from the 2012 survey included
nutrition recommendation, nutrition composition, nutri-
tion function, food safety and environmental knowledge
scores. A total nutrition knowledge score was then derived
by summing the nutrition recommendations, nutrition
composition and nutrition function scores (Table 2).
No food label knowledge scores were calculated for
the 2012 survey. Demographic and background informa-
tion was also coded in a similar manner to Study 1 with
the exception of three new questions: Did you study
home economics or a similar subject at secondary school
(e.g. domestic science, food technology, etc.)? (no = 2,
yes = 1, I can’t remember = 3), and, what do you remember
most about this subject in school? Recipes (coded as 1),
cooking techniques, e.g. how to simmer or sauté (coded
as 2), safety in the kitchen (coded as 3), preparation tech-
niques, e.g. measuring, dicing (coded as 4), budgeting
(coded as 5), something else (coded as 6) and did you
learn about food-related topics (e.g. nutrition, diet and
health relationships, environmental impact of food pro-
duction) in any other subjects at school? (no = 2, yes = 1).
Data analysis
All statistical procedures were conducted via SPSS version
21 (SPSS, 2012). The demographic and home economics
study characteristics of the respondents to both surveys
were summarized by frequency counts (Table 1). The
percentages of respondents who answered each item
correctly were also calculated (available from the corre-
sponding author). Stepwise multiple regressions were
carried out on each of the knowledge scores in Studies 1
and 2 with age, gender, educational level, presence/ab-
sence of children under 18 years of age in the household,
and school health or home economics as predictor vari-
ables (Table 2). These were repeated within each age
band (18–29, 30–39, 40–49, 50–59, 60 years and over)
and State (Tables 3 and 4). Finally, Study 2 respondents’
recall of the topics they had learned from their home eco-
nomics education was compared in a cross-tabulation
analysis (Table 5).
RESULTS
Participants in both surveys were of similar ages (Table 1),
but fewer nominated that they had studied home econom-
ics or a similar subject in the 2012 survey. About one-third
of the respondents in both surveys had one or more chil-
dren under 18 living with them. Similarly, approximately
one-third of the respondents were university graduates.
The genders were approximately equally represented in
both surveys.
The results of the multiple regression analyses of the
knowledge scores across the two studies were similar, al-
lowing for the smaller number of items and the narrower
definition of home economics (which did not include
health) in Study 2. The amounts of variance explained
by the predictors in Study 1 were generally higher than
that in Study 2. Age was positively associated with all of
the knowledge scores in both studies. Gender was positively
associated with all the scores except Food Label knowl-
edge and Food Safety knowledge and negatively with
Environmental and Ethics knowledge in Study 2, and
Food Label knowledge in Study 2. Overall, women tended
to know more about nutrition and safety issues than men.
General education was also positively linked to most
scores in both studies except for Food Label knowledge
and Environmental and Ethics knowledge in Study 2.
In both studies, respondents who had undertaken
home economics at school recalled more about food issues
than those who had not (Table 2). The findings in Study 2,
which focused on school home economics education, were
similar to those in Study 1, which focused on school health
or home economics education. The size of the regression
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6. Table 3: Study 2: differences between respondents who had undertaken or not undertaken home economics (or a similar subject) at school by age group
Age groups Nutrition function
knowledge score
Standardized β
Nutrition
recommendation
knowledge score
Standardized β
Nutrition composition
knowledge score
Standardized β
Total nutrition
knowledge score
Standardized β
Food label
knowledge score
Standardized β
Food safety
knowledge score
Standardized β
Environment and
ethics knowledge score
Standardized β
Study 1, 2011
18–29
n = 467
0.216**** 0.195**** 0.153*** 0.213**** 0.122** 0.098* 0.133**
30–39
n = 417
– 0.175*** 0.183**** 0.206**** 0.207**** 0.141*** 0.111**
40–49
n = 418
0.219**** 0.189**** 0.173**** 0.229**** 0.240**** 0.172**** 0.128**
50–59
n = 400
– – – 0.138** 0.181**** – –
60 and over
n = 320
– – – – – 0.158** 133*
Study 2, 2012
18–29
n = 239
0.198*** 0.215*** 0.193*** 0.233**** – 0.334**** 0.201***
30–39
n = 392
0.154*** 0.101* 0.126** 0.133** – 0.145*** 0.218****
40–49
n = 416
0.128** 0.141*** – 0.123** – – 0.124**
50–59
n = 419
0.148*** – – – – 0.105*
60 + years
n = 680
– – – – – – –
Notes: The coefficients in the columns are the standardized regression coefficients (β) between each knowledge score and the school health or home economics variable across age groups in the 2012 Food Knowledge Survey; positive
regression coefficients indicate higher scores among those who had undertaken home economics or a similar subject at school. –, not significant.
*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.000.
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7. Table 4: The associations of food knowledge scores with school health or home economics across the States of Australia in Studies 1 and 2
Nutrition function
knowledge score
Standardized β (P)
Nutrition
recommendation
knowledge score
Standardized β (P)
Nutrition
composition
knowledge score
Standardized β (P)
Total nutrition
knowledge score
Standardized β
(P)
Food label
knowledge score
Standardized β (P)
Food safety
knowledge score
Standardized β (P)
Environment and
ethics knowledge
score
Standardized β (P)
10 items total
nutrition
knowledge score
Standardized β (P)
Study 1, 2011
NSW
n = 640
0.191**** 0.168**** 0.117*** 0.156**** 0.186**** 0.134*** 0.142***
VIC
n = 482
0.176**** 0.173**** 0.124** 0.098* 0.175**** 0.116** 0.090*
QLD
n = 406
– – – 0.103* 0.113** – –
SA
n = 157
– 0.281*** 0.287**** 0.390**** 0.343**** 0.222** –
WA
n = 206
0.221*** 0.406**** 0.307**** 0.347**** 0.436**** 0.232*** 0.230***
Study 2, 2012
NSW
n = 587
0.094* 0.110** 0.100** 0.107** – – 0.100** 0.085*
VIC
n = 561
0.130*** – 0.102** 0.111** – 0.154**** 0.146*** –
QLD
n = 409
0.140*** 0.113* – 0.117** – – 107* 0.111**
SA
n = 208
– – – – – 0.184*** – –
WA
n = 199
– 0.223** 0.151* 0.201*** – 0.145* – –
Notes: The coefficients in the columns are the standardized regression coefficients (β) from univariate analysis between each knowledge score and the school health or home economics variable. The results for the Northern Territory
and Australian Capital Territory and Tasmania are not shown due to insufficient samples sizes. Standardized regression coefficient; –, not significant.
*p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.000.
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8. coefficients associated with school health or home eco-
nomics education in Study 1 was similar to those asso-
ciated with gender, greater than those associated with
general education or the presence of children but less
than the relationships between age and food knowledge.
In Study 2, similar relationships were observed though
the size of the associations of home economics was smaller
than those associated with demographic variables (Table 2).
The regression analyses of the home economics/health
studies associations with the various scores by age group
were similar between the two studies, with the relation-
ships generally being smaller in Study 2 (Table 3).
Overall, the findings suggest that people up to age 50
who had undertaken home economics education tended
to have higher scores on most of the scales. Total nutrition
knowledge and environmental and ethical knowledge
appeared to extend to the age of 60 (‘over sixties’).
The comparisons across the larger States of Australia
showed some distinct differences, especially in Study 1
with regard to the higher regression coefficients observed
among respondents who had been educated in Western
Australia (Table 4). This trend was not repeated for
South Australia in Study 2, but the Western Australian
regression coefficients appear to be larger than those
associated with the other States as in Study 1. Within
the findings for each State, it is clear that some regression
coefficients were larger than others. For example, in Study
1 the Victorian results show that nutrition function
knowledge, nutrition recommendations knowledge and
food label knowledge were associated with bigger differ-
ences between home economics educated and non-home
economics educated respondents than the other scores
(Table 4). In Study 2, however, these differences were
attenuated.
In Study 2, an additional question was included: What
do you remember most about home economics at school?
The greatest number of respondents chose cooking techni-
ques (39.4%, Table 5) followed by preparation techniques
(24.5%), with budgeting being the least recalled (4.3%).
There were major differences in the age groups’ recall of
cooking techniques. Almost four times as many respon-
dents aged 60 and over recalled cooking techniques com-
pared with those aged 18–29 years (Table 5). In contrast,
over three times as many 18–29-year olds compared with
the over sixties recalled safety in the kitchen (Table 1). No
statistically significant differences in recalls were asso-
ciated with either State of residence or the presence of ab-
sence of children under 18 years in the household. Ninety
respondents mentioned other things they remembered
about their HE courses. Sixteen remembered all the listed
topics, 28 reported they could not remember anything, 13
mentioned cooking or sewing, 4 recalled food manufac-
turing or farming, 17 had negative memories either
being bored or disliking the teacher and 12 mentioned
miscellaneous topics.
DISCUSSION
The demographic characteristics of the two samples were
similar. The findings of greater nutrition and safety knowl-
edge among women and the generally greater knowledge
of older and higher educated people are consistent with
those from previous studies (gender: 18, 19, 20, 21, 22,
23; age: 19, 20, 21, 24, 25; education: 20, 21, 27, 28).
These findings support the external validity of the two
studies. The lower standardized regression coefficients ob-
served in Study 2 may be a consequence of the lesser num-
ber of items making up the knowledge scores in that study.
The findings from both studies strongly suggest that
health or home economics education is related to the vari-
ous forms of food knowledge. The replication of the find-
ings from Study 1 by the shorter scores from Study 2
Table 5: Percentages of respondents across age groups who remembered aspects of their home economics education in
Study 2 (2012)
Study 2, 2012 Age groups
18–29, % (N) 30–39, % (N) 40–49, % (N) 50–59, % (N) 60 and over, % (N)
What do you remember most about home economics at school?
Recipes 22.9 (24) 18.7 (36) 18.4 (38) 17.3 (32) 11.5 (24)
Cooking techniques 10.5 (11) 23.3 (45) 28.0 (58) 37.3 (69) 39.4 (82)
Preparation techniques 21.9 (23) 21.2 (41) 24.6 (51) 19.5 (36) 24.5 (51)
Cooking and preparation 32.4 (34) 44.5 (86) 52.6 (109) 66.8 (105) 63.9 (133)
Safety in the kitchen 34.3 (36) 20.2 (39) 11.6 (24) 8.1 (15) 10.1 (21)
Budgeting 1 (1) 6.7 (13) 4.8 (10) 3.2 (6) 4.3 (9)
Something else 9.5 (10) 9.8 (19) 12.6 (26) 14.6 (27) 10.1 (21)
χ2
(P) 83.343 (0.001)
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9. suggests that these relationships are fairly stable between
samples, and the size of the relationships appears similar
to those associated with general education and the pres-
ence of children in the household. The interpretation of
these findings, however, requires caution. At face value,
the results suggest that home economics (or similar) edu-
cation may result in people having food knowledge than
those who have not undergone such education. Given
the content of home economics education, this is an entire-
ly reasonable explanation. However, other explanations
of these correlations may be equally plausible. For ex-
ample, respondents who were more interested in food
and health matters may have selected to undertake these
forms of education or may have been more attentive to
the information provided in the various courses they
undertook.
Furthermore, the respondents may have continued to
learn about food and health interests throughout life
because of their interest in these areas. Longitudinal or
experimental approaches are required to clarify the direc-
tion of the home economics–food knowledge relationships
observed in these studies. Nevertheless, the findings do
suggest that home economics education may have effects
on people’s food knowledge long after their schooling
has been completed. To our knowledge, only McCarthy
et al.’s study of Irish students’ food safety knowledge has
shown similar links with home economics education
(McCarthy et al., 2007).
The observation that people who had undertaken
home economics education at school had higher levels of
various types of food knowledge than others many years
afterwards (Table 3) suggests that this form of education
may have long-term effects. Again, this may be due, at
least in part, to a prior interest in food and health matters,
but it is consistent with the notion that home economics,
with its high relevance to daily life issues and practices,
communicates learning for a lifetime. Again, more inves-
tigation is required in future studies to examine, for ex-
ample, the reasons for some types of knowledge having
greater longevity than others (Table 3) and whether home
economics education ‘primes’ people to continue learning
about food and health issues after they have left school.
Cardemil et al.’s work on the skills required to recover
from failures in Philadelphia school children suggests that
the provision of skills during education enables people to
learn from their mistakes and experiences to develop skills
(Cardemil et al., 2007). Similar skills development may
occur in food transformation processes such as cooking,
the provision of basic skills during education, allowing
people to continue to develop them during their lives.
The State comparisons shown in Table 4 provide some
evidence to suggest that local conditions may affect
respondents’ food knowledge. Both Western Australia
and South Australia in Study 1 displayed stronger associa-
tions of home economics education with several forms of
food knowledge. This was only partially replicated in
Study 2, where the associations among the Western
Australian group of respondents were generally higher
than among the other respondents. One possible explan-
ation may be differences in the content of the home eco-
nomics curricula taught in the States or differences
between the ways these curricula were taught, though des-
pite searches of the Australian home economics literature
and discussion with experienced home economics educa-
tors, these remain elusive. Although these associations
were not very stable between the studies (perhaps because
of the use of differing knowledge measures), they lend sup-
port to the view that home economics education results in
higher levels of food knowledge.
Further evidence about the likely effects of home eco-
nomics education was provided by the respondents in
Study 2, who were asked what they remembered from
their school home economics subjects (Table 5). The two
major age group differences in these reports suggest that
over the last 40 years, cooking skills have become less sa-
lient and food safety more salient. This appears to mirror
the changes which have taken place in home economics
curricula during this time (Curriculum Corporation,
1996). This again supports the view that home economics
teaching has long-term effects on food knowledge.
Implications for teaching
These findings support the influence of home economics
curricula on the general population of consumers over
several decades. They provide some evidence to support
the maintenance and extension of home economics teach-
ing in Australian schools. The age group differences in re-
called learning (Table 5) suggest that the shift towards
food technology that occurred in the curriculum
20 years ago may have weakened the emphasis on cooking
and preparation in favour of safety issues, though this
might also be a result of the drift towards risk aversion
in Anglo societies (Furedi, 2005). Overall, the State and
age group differences in food knowledge and the differ-
ences in the recall of home economics learning between
the age groups suggest that home economics teaching
has lasting effects.
Limitations and further research
These two studies have several limitations that influence
the interpretation of these findings. First, they were cross-
sectional studies and, as noted above, causal attributions
cannot be made from them alone. Further examination
HE education and food knowledge 9
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10. of the influence of home economics teaching on food
knowledge and skills is required. A longitudinal monitor-
ing study of a representative sample of students over 10 or
20 years or longer would help establish the causal role of
home economics education. Alternatively, randomized
control trials of home economics programmes with long-
term follow-ups may provide similar evidence in a shorter
time. A second limitation lies in the nature of the food
knowledge scores. Although these were composed of vali-
dated items, they could be improved. In particular, more
environmental knowledge items are required. Further,
the relevance of the items to individuals’ lives needs to
be assessed. For example, several food safety items to do
with the cleaning of chopping boards may be redundant
with changes in the meat supply, chopped meat being
readily available for cooking (Wills et al., 2013). The on-
line quota samples might restrict the generalizability of the
findings although the replication of the findings across the
two studies suggests this was not a serious problem.
CONCLUSIONS
The two studies confirmed the associations of age, gender
and general educational status with various forms of food
knowledge. They also showed that home economics (and
similar) education was associated with higher levels of
food knowledge among several age groups. The differen-
tial influence of home economics education between
States, and the differential recall of home economics
themes across age groups, suggests that different curricula
have different effects on food knowledge. Overall, sub-
stantial evidence suggests that home economics education
brings about long-term changes in food knowledge.
Further research is required to confirm and extend these
findings.
FUNDING
This research was supported by an Australian Research
Council Discovery grant (DP1094493).
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